With applications ranging from diagnostic procedures to radiation therapy, the importance of high-performance medical imaging is immeasurable. As a result, new high-performance medical imaging technologies are continually being developed. Digital medical imaging technologies represent the future of medical imaging. Digital medical imaging systems are capable of producing far more accurate and detailed images of an anatomical object than conventional, film-based medical imaging systems. Such digital medical imaging systems also allow for image enhancement once an anatomical object has been scanned, further enhancing their usefulness.
The flat-panel digital radiographic imaging detectors available today typically have a maximum imaging size of about 40 cm×40 cm. Often, an area of interest larger than 40 cm×40 cm must be imaged. In such cases, several sub-images are taken and combined to form a single, larger image of the area of interest. For example, if a 90 cm spinal image must be taken, three separate sub-images of the spine must be taken and combined to form a single, larger image. This presents a challenge because a wide range of anatomical thicknesses must be represented. Typically, a spinal image includes very thin anatomical parts, such as the c-spine, and very thick anatomical parts, such as the abdomen.
When sub-images are acquired using auto-exposure techniques and processed individually, the auto-exposure techniques ensure that anatomical thickness differences are compensated for and accurately represented. The combined image will then have a sufficiently narrow dynamic range to be displayed as is. Referring to FIGS. 1 and 2, however, the combined image 10 will include different brightness or intensity bands, the boundaries of which correspond to the boundaries of the sub-images 12. These low-frequency band artifacts 14 are caused by the fact that the brightness or intensity levels of each of the sub-images 12 are matched only where they are measured, namely in the center portion 16 of each of the sub-images 12. The low-frequency band artifacts 14 are bothersome to those analyzing the combined image 10, especially in the junction regions, and may obscure anatomical detail.
When sub-images are acquired using fixed techniques, or if the sub-images are normalized with regard to exposure, the different brightness or intensity bands are not visible. Referring to FIG. 3, however, the dynamic range of the combined image 10 is increased and some portions 18 of the combined image 10 become saturated. Conventional image-equalization algorithms may compensate for this effect, but extreme parameters must be used, leading to potentially strong distortions in the area of interest, as such algorithms are typically designed for the specific detector size.
Thus, what is needed is a pre-processing imaging method that compensates for dynamic range in the direction(s) of the combined scan, such that the desirable effects of the conventional image-equalization algorithms are preserved.